April 25-27, 2017

San Francisco, USA

 

Day One
Wednesday, April 26, 2017

Day Two
Thursday, April 27, 2017

08.20
Chairman’s Opening Remarks: An Overview of the RNA-Seq Field & Looking Towards the Next Generation of RNA Technologies

  • Paul Kayne Director, Genomics, Bristol-Myers Squibb Co

Understanding the Transcriptome Through Emerging Sequencing Concepts

08.30
A 5’Complete Transcriptomic Atlas & its Applications in Studies of Long Non-Coding RNA

  • Chung-Chau Hon Research Scientist, RIKEN Center for Life Science Technologies

Synopsis

  • Generating a novel and comprehensive catalog of high-confidence 5’complete human long non-coding RNA (lncRNA) genes by integratingFANTOM5 CAGE data with RNA-Seq
  • Clarifying the heterogeneity of lncRNAs to determine the derivation of intergenic lncRNAs as enhancer-like regions rather than from promoters
  • Incorporating genetic and expression data to identify potential roles in diseases and gene regulation for thousands of lncRNAs

09.00
A Head-to-Head Comparison Between Total vs. mRNA-Sequencing

  • Shanrong Zhao Director, Computational Biology and Bioinformatics, Pfizer Inc.

Synopsis

  • Evaluating these two sequencing protocols
  • Exploring the real advantages and disadvantages of total RNA-Seq

09.30
Sensitive & Comprehensive Genome-Wide Expression Profiling Directly from Total RNA

Synopsis

  • Gene expression analysis of target model systems is required to understand the genetic changes associated with biological responses
  • We show that the combination of RT-PCR amplification with next generation deep sequencing provides a more sensitive and robust approach for transcriptome profiling than standard RNA-Seq
  • The RT-PCR step with targeted primers enables the profiling assay to generate highly specific data, even with mouse xenograft models, directly from total RNA

09.45
Panel Discussion: Specialized RNA Sequencing Methods with Applications to RNA Life Cycles & Drug Development

  • Bin Tian Professor of Microbiology, Biochemistry & Molecular Genetics, Rutgers Cancer Institute of New Jersey
  • Paul Kayne Director, Genomics, Bristol-Myers Squibb Co
  • Shanrong Zhao Director, Computational Biology and Bioinformatics, Pfizer Inc.

Synopsis

  • Discussing a role for nascent RNA-Seq as a Diagnostic and Prognostic Tool
  • Analyzing 3’vs. 5’ sequencing, applications utility and robustness
  • Understanding how to map polymerase on the template
  • Realizing the benefits from a low posttranscriptional noise

10.30
Morning Refreshments & Speed Networking

Understanding RNA Processing to Further Drug Development

11.30
RNA-Seq Profiling of Low Numbers of Tumor-Resident Human Immune Cells

Synopsis

  • Identifying the minimum sample size for low-input RNA-sequencing
  • Evaluation of SMARTer/Nextera vs. TruSeq on sorted human immune cells from blood and tumor
  • Profiling small numbers of sorted immune populations from clinical tumor tissues

12.00
The Command Line is Compromise: A New Paradigm for Single Cell RNA-Seq Analysis

Synopsis

  • The Command Line is Compromise: A New Paradigm for Single-Cell RNA-Seq Analysis
  • We have developed a new analysis paradigm for gene expression analysis using bidirectional cell population-gene set visualization, which enables bench scientists to derive insight from RNA-Seq data, particularly single cell RNA-Seq; share their gene sets and discovery process reproducibly; pre-process and normalize how they see fit; and requires no command line or bioinformatics expertise.
  • Using a publicly available data set from a study of metastatic melanoma and intuitive supervised and unsupervised analyses, we show that layers of depth beyond traditional immunological phenotyping are possible and show reduction in analysis time from >4
    hours to less than 30 seconds.
  • We present an innovative, rapid, intuitive analysis paradigm to harness the power of single cell RNA-Seq and gene expression studies.

12.30
Deconvoluting RNA-Sequencing Profiles into Cellular Subtypes for Oncology

  • Paul Rejto Executive Director & Head of Translational Research, Pfizer Inc.

Synopsis

  • Understanding that cancer immunotherapies are highly variable from patient to patient and that RNA-Seq can provide novel insights into cancer immune subtypes
  • Realize the emerging role of RNA-Seq in developing predictive and early pharmacodynamics biomarkers for cancer immunotherapy

13.00
Lunch & Networking

Novel Sequencing Methods for Disease Profiling

14.00
How Merck has been Leveraging Omicsoft in Supporting Clinical and Discovery Translational Research

  • Jianchao (JC) Yao Associate Principal Scientist, Computational Genomics & Genetics, Merck & Co

Synopsis

  • Omicsoft RNA-Seq pipelines (RNA-Seq transcriptome profiling, miRNA-Seq, Single-Cell RNA-Seq, etc) used at Merck
  • Integrating PD1 genomics biomarker data (RNA-Seq, Whole Exome Sequencing, NanoString and MSI) using the Omicsoft Land technology

14.30
Using 3’ Sequencing to Understand Human Diseases

  • Bin Tian Professor of Microbiology, Biochemistry & Molecular Genetics, Rutgers Cancer Institute of New Jersey

Synopsis

  • Exploring the mechanism utility and consequence of dysregulation of 3’ termination in disease pathogenesis and spread
  • Insights into how 3’ regulation is related to health and disease
  • Recent data into cancer, metastasis and neurological diseases

15.00
KAPA RNA HyperPrep: Improved Performance with Degraded Inputs & Tumor Profiling Applications

Synopsis

High-resolution RNA analysis using next-generation sequencing (RNA-seq) is a rapidly growing application in disease research. The quality of RNA extracted from biological
specimens is highly variable and yields are often low, thus impacting the ability to generate high-quality sequencing libraries.

In this presentation, we will:

  • Discuss improvements in the library preparation workflow
  • Provide guidance on working with low input & degraded samples
  • Demonstrate improved detection of differential expression in tumor profiling

15.30
Afternoon Refreshments & Dedicated Poster Session

16.00
Integrating Big Data for RNA Processing – From Computational Modeling, Through the Wet Lab, to Patients

  • Yoseph Barash Assistant Professor, Perelman School of Medicine University of Pennsylvania

Synopsis

  • Review state of the art in RNA splicing detection, quantification, and prediction algorithms
  • Showcase examples of how machine learning algorithms are used to derive new findings in RNA processing and disease associated transcript variations that are then verified experimentally
  • Address challenges and directions in Big Data analysis in the field

16.30
Elucidating Transcriptome Complexity & Alternative Isoform Variation Using Massive RNA-Seq Data

  • Yi Xing Professor, Microbiology, Immunology, & Molecular Genetics, UCLA

Synopsis

  • Demonstrating RNA-Seq as a powerful technology for transcriptome-wide profiling of mRNA isoform variation resulting from alternative RNA processing and modifications
  • Identifying novel biomarkers and therapeutic targets of cancer through global analysis of mRNA isoform variations in clinical cancer RNA-Seq data sets
  • Exploring robust and efficient statistical and computational methods required for isoform analysis using massive RNA-Seq datasets

17.00
Round Tables

  • Rob Currie Chief Technology Officer, UCSC Genomics Institute
  • Paul Kayne Director, Genomics, Bristol-Myers Squibb Co
  • Garry Nolan Rachford and Carlota Harris Professor , Stanford University
  • Yi Xing Professor, Microbiology, Immunology, & Molecular Genetics, UCLA

Synopsis

  1. Data Processing & Informatics Management, Rob Currie
  2. The Utility of Non-Coding RNA in Drug Development, Paul Kayne
  3. What’s Necessary for Clinical Validation: Controlling the Statistical Variables, Garry Nolan
  4. RNA Based Modifications: Exploring a Potential Role in Drug Development, Yi Xing

17.30
Chairman’s Closing Remarks

17.35
Close of Day One

QIAGEN Sponsored Evening Reception